Time based device clustering for domestic power scheduling

Article history: Received 5 September 2016 Received in revised form 14 October 2016 Accepted 18 October 2016 Domestic consumers can reduce their electricity expenditures by shifting their loads to slots of low power usage during demand response (DR) in a smart grid (SG) power system. Efficient shifting of loads can be used to reduce the peak-to-average (PAR) of power network, which is highly desirable for the reliability of SG. Methodologies available in literature only address the problem of power scheduling for a small set of consumers and underperforms for large population. This paper presents clustered community based home energy management system (CCHEMS), which performs better for a huge consumer set. CCHEMS is based on clustering consumer devices according to operating time overlap. Activation time slots (ATS) of clustered devices under user defined constraints are subjected to particle swarm optimization (PSO) to attain optimum power demand. Real time electricity price (RTEP) and modified inclined block rate (IBR) is employed to contain the power demand under appropriate limits. Results confirm that CCHEMS is better than non-clustered optimization, 9% in cost reduction and 24% in PAR trimming for a population of 1000 consumers.